Description
This pipeline maps SNOMED codes to their corresponding ICDO codes via a direct dictionary lookup.
Wraps the snomed_icdo_mapper_20260901 mapper, trained on SNOMED CT US Edition 20260901 crosswalk data.
Live Demo Open in Colab Copy S3 URI
How to use
from sparknlp.pretrained import PretrainedPipeline
snomed_pipeline = PretrainedPipeline("snomed_icdo_mapping_pipeline_20260901", "en", "clinical/models")
data = spark.createDataFrame([["10013000"]]).toDF("text")
result = snomed_pipeline.transform(data)
from johnsnowlabs import nlp, medical
snomed_pipeline = nlp.PretrainedPipeline("snomed_icdo_mapping_pipeline_20260901", "en", "clinical/models")
data = spark.createDataFrame([["10013000"]]).toDF("text")
result = snomed_pipeline.transform(data)
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val snomed_pipeline = PretrainedPipeline("snomed_icdo_mapping_pipeline_20260901", "en", "clinical/models")
val data = Seq("10013000").toDF("text")
val result = snomed_pipeline.transform(data)
Results
| snomed_code | icdo_code | all_k_resolutions |
|--------------:|:------------|:--------------------|
| 10013000 | C40.2 | C40.2::: |
| 102291007 | C49.2 | C49.2:::C49.5 |
| 128501000 | C49.5 | C49.5:::C76.3 |
Model Information
| Model Name: | snomed_icdo_mapping_pipeline_20260901 |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 6.4.1+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 275.7 KB |
Included Models
- DocumentAssembler
- Doc2Chunk
- ChunkMapperModel